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utkuufuk.com | ||
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www.nyckel.com
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| | | | | A confusion matrix is a great way of visualizing your machine learning classification models. This tool makes it easy to build them. | |
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www.oranlooney.com
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| | | | | [AI summary] The article discusses unsupervised learning, focusing on the Gaussian Mixture Model (GMM) and the Expectation-Maximization (EM) algorithm. It explains how GMM uses the EM algorithm to cluster data without labeled examples, and demonstrates its application on the Iris dataset. While GMM successfully finds clusters, the agreement with true labels is only 96% for one random seed, with variability across trials. The article highlights the limitations of unsupervised learning, including arbitrary complexity parameters, lack of hard metrics, and subjective model interpretation. It concludes that unsupervised learning is valuable for exploratory analysis and representation learning but requires more expertise and domain input compared to supervised met... | |
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hadrienj.github.io
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| | | | | In this post, we will learn about the Moore Penrose pseudoinverse as a way to find an approaching solution where no solution exists. In some cases, a system ... | |
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ben.bolte.cc
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| | | A quick introduction to using Theano for deep learning, from the bare-bones to a full neural network. | ||
